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Biology subjects

Henriot, P.

Publications and source records attributed to Henriot, P..

2 recordsLinked to original sources

COVID-19 pandemic responses may impact the spread of antibiotic-resistant bacteria: a modelling study

Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built in into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus- bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.

evolutionary biology↗

Modelling the impact of urban and hospital wastewaters eco-exposomes on the antibiotic-resistance dynamics.

Antibiotic-resistance emergence and selection have become major public health issues globally. The presence of antibiotic resistant bacteria (ARB) in natural and anthroposophical environments threatens to compromise the sustainability of care in human and animal populations. This study was undertaken to develop a simple model formalizing the selective impact of antibiotics and pollutants on the dynamics of bacterial resistance in water and use the model to analyze longitudinal spatiotemporal data collected in hospital and urban wastewaters. Longitudinal-sampling data were collected between 2012 and 2015 in four different locations in Haute-Savoie, France: hospital and urban wastewaters, before and after water-treatment plants. Concentration in three different types of compounds: 1) heavy metals 2) antibiotics and 3) surfactants; and abundance of 88 individual genes and mobile genetic elements, mostly conferring resistance to antibiotics, were simultaneously collected. A simple hypothesis-driven model describing the weekly ARB dynamics was proposed to fit available data by assuming normalized gene abundance to be proportional to ARB populations in water. Compounds impacts on the dynamics of 17 genes found in multiple sites were estimated. We found that while mercury and vancomycin had relevant effects on ARB dynamics, respectively positively affecting the dynamics of 10 and 12 identified genes, surfactants antagonistically affected genes dynamics (identified for three genes). This simple model enables analyzing the relationship between resistance-gene persistence in aquatic environments and specific compounds inherent to human activities. Applying our model to longitudinal data, we identified compounds that act as co-selectors for antibiotic resistance. HighlightsO_LIWe analyzed longitudinal wastewater resistance genes and environmental data C_LIO_LIWe developed a simple hypothesis-driven model to assess resistance selection C_LIO_LIMercury and vancomycin were key drivers of antibiotic resistance in wastewater C_LI

microbiology↗